This article shows that contemporaneous and lagged air pollution negatively affects the likelihood of German individual investors to log in and trade in their brokerage accounts, using intraday data and controlling for investor-, weather-, traffic-, and market-specific factors. A 1 SD increase in air pollution leads to a 1.3 percent reduction in the probability of logging in, which is larger than the response to a 1 SD increase in sunshine. We argue that changes in air pollution affect productivity in cognitively demanding tasks, such as trading. Our results are robust to macroeconomic productivity shocks, nonlinearities, or measurement error.

We investigate individual investors' decisions under time-varying ambiguity (VVIX) using plausibly exogenous forced mutual fund liquidations at a German brokerage. Investors reinvest 87% of forced liquidations when the refund occurs on a day of low ambiguity and 0% when it occurs on a day of high ambiguity. Instead of reinvesting, investors become inert and keep the refund in their cash holdings. The effect reverses approximately six months after the liquidation. If investors reinvest, they decrease their risk-taking under ambiguity. Our results are not driven by risk, rebalancing decisions, experiencing losses, or attention and are robust to alternative measures of ambiguity.

We explore the impact of weather on trading by individual investors. Over a time span of 94 months, we analyze daily trading records of individual investors. Controlling for various investor- and market-specific factors, we find a two-fold effect of weather. We first observe that investor sentiment, as measured by purchases relative to sales, is significantly higher on days with good weather. In addition, we find that retail investors generally trade more on bad weather days. This result is consistent with the notion that retail investors incur an opportunity cost for spending time trading on days with good weather.

We analyze how individuals reinvest realized capital gains and losses exploiting plausibly exogenous sales due to mutual fund liquidations. Individuals reinvest 83% if a forced sale results in a gain relative to the initial investment; but reinvest only 40% in the event of a loss. This difference is statistically significant for more than six months and arises because many individuals forced to realize a loss choose not to reinvest anything and some even exit the stock market altogether. Individuals treat realized losses differently from paper losses and are discouraged from investing more and participating in the stock market.

Utilizing transaction-level financial data, we explore how household consumption responded to the onset of the COVID-19 pandemic. As case numbers grew and cities and states enacted shelter-in-place orders, Americans began to radically alter their typical spending across a number of major categories. In the first half of March 2020, individuals increased total spending by over 40% across a wide range of categories. This was followed by a decrease in overall spending of 25%–30% during the second half of March coinciding with the disease spreading, with only food delivery and grocery spending as major exceptions to the decline. Spending responded most strongly in states with active shelter-in-place orders, though individuals in all states had sizable responses. We find few differences across individuals with differing political beliefs, but households with children or low levels of liquidity saw the largest declines in spending during the latter part of March.

The 2020 CARES Act directed large cash payments to households. We analyze households’ spending responses using data from a Fintech nonprofit, exploring heterogeneity by income, recent income declines, and liquidity as well as linked survey responses about economic expectations. Households respond rapidly to payments, with spending increasing by about $0.14 per dollar during the first week and plateauing around 0.25–0.30 over 3 months. In contrast to previous stimulus programs, we see little response of durables spending. Households with lower incomes, greater income declines, and less liquidity display stronger responses whereas households that expect employment losses and benefit cuts display weaker responses.